2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)最新文献

The Balance Ability of Fallers and Non-Fallers in Psychiatric Patients at a Long Term Care Unit 长期护理病房精神病患者跌倒者与非跌倒者的平衡能力

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-12-16 DOI: 10.1109/BIBE.2016.58

San-Ping Wang, Jen-Suh Chern, Jer-Hao Chang, Bo-Jian Wu, Hsiao-Ju Sun, Jiunn-Ying Liou

引用次数: 0

Comparison of Motion Sickness-Induced Cardiorespiratory Responses between Susceptible and Non-susceptible Subjects and the Factors Associated with Symptom Severity 运动病易感与非易感受试者的心肺反应及症状严重程度相关因素的比较

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-12-16 DOI: 10.1109/BIBE.2016.16

Chien-Liang Chen, Ping-Chia Li, C. Chuang, Chi-Wen Lung, Jing-Shia Tang

{"title":"Comparison of Motion Sickness-Induced Cardiorespiratory Responses between Susceptible and Non-susceptible Subjects and the Factors Associated with Symptom Severity","authors":"Chien-Liang Chen, Ping-Chia Li, C. Chuang, Chi-Wen Lung, Jing-Shia Tang","doi":"10.1109/BIBE.2016.16","DOIUrl":"https://doi.org/10.1109/BIBE.2016.16","url":null,"abstract":"This study aimed to examine the correlations between susceptibility to motion sickness and pulmonary function and aerobic capacity. We supposed that people with different susceptibilities to motion sickness differ in their cardiorespiratory responses. Thirteen healthy young men were recruited. They were asked to complete a motion sickness history questionnaire and were divided into susceptible and non-susceptible groups. A rotary chair was rotated for 10 minutes at 20 rpm to induce motion sickness. After the rotation, Graybiel's diagnostic criteria were used to grade the severity of motion sickness. This study also conducted evaluations of cardiorespiratory responses. Participants underwent a pulmonary function test and an exercise test to evaluate aerobic capacity. A generalized estimating equation was used to analyze the correlation between Graybiel's scores and the pulmonary function and exercise test results. The differences between the two groups were analyzed for the physiological parameters measured. The results indicated higher severities of motion sickness in participants with lower values of maximum voluntary ventilation (MVV). Moreover, the group of susceptible participants demonstrated significantly higher Graybiel's scores and stronger cardiorespiratory responses, significant interaction effects were observed in oxygen consumption, carbon dioxide production (VCO2), ventilation, and respiratory rate. To summarize, MVV is proposed as a reference index for evaluating susceptibility to motion sickness. Severe motion sickness in susceptible participants is suggested to be related to hyperventilation, which causes excessive VCO2.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114591776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Using Deep Learning with Position Specific Scoring Matrices to Identify Efflux Proteins in Membrane and Transport Proteins 使用深度学习和位置特定评分矩阵来识别膜和运输蛋白中的外排蛋白

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.69

Semmy Wellem Taju, N. Le, Yu-Yen Ou

{"title":"Using Deep Learning with Position Specific Scoring Matrices to Identify Efflux Proteins in Membrane and Transport Proteins","authors":"Semmy Wellem Taju, N. Le, Yu-Yen Ou","doi":"10.1109/BIBE.2016.69","DOIUrl":"https://doi.org/10.1109/BIBE.2016.69","url":null,"abstract":"In several years, deep learning is a new area of machine learning field, which is the motivation of developing machine learning near to artificial intelligent. The neural networks belongs to deep learning are progressively important ideas in a variety of fields with great performance. Accordingly, utilization of deep learning in bioinformatics to enhance performance is very important. Convolutional neural networks is a network of deep learning which is claimed to be the best model to solve the problem of object recognition and detection utilizing GPU computing. In this study, we try to use CNN to identify efflux proteins in membrane and transport proteins, which is a famous problem in bioinformatics field. We construct the CNN from PSSM profiles with CUDA and Keras package based on Theano backend. Finally this approach achieved a significant improvement after we compare with the previous paper on efflux proteins. The proposed method can serve as an effective tool for identifying efflux proteins and can help biologists understand the functions of the efflux proteins. Moreover this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115278007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Host-Pathogen Protein Interaction Prediction Based on Local Topology Structures of a Protein Interaction Network 基于蛋白质相互作用网络局部拓扑结构的宿主-病原体蛋白质相互作用预测

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.26

Jira Jindalertudomdee, M. Hayashida, Jiangning Song, T. Akutsu

{"title":"Host-Pathogen Protein Interaction Prediction Based on Local Topology Structures of a Protein Interaction Network","authors":"Jira Jindalertudomdee, M. Hayashida, Jiangning Song, T. Akutsu","doi":"10.1109/BIBE.2016.26","DOIUrl":"https://doi.org/10.1109/BIBE.2016.26","url":null,"abstract":"Understanding how pathogen's proteins interact with its host's proteins is the key concept for understanding pathogen's infection mechanism, which can lead to the discovery of improved therapeutics for treating infectious diseases. Several studies suggest that proteins from various pathogens tend to interact with human proteins involved in the same biological pathway. This implies that pathogens are inclined to target host's proteins with similar function. In addition, conservation between a protein's function and its local topological structure in a protein-protein interaction network (PIN) has been previously characterized. This leads to the hypothesis that pathogens target the host's proteins with a similar local topological structure in a PIN. In this work, this hypothesis is examined by adding a graphlet degree vector of a protein in the human PIN as a feature in the prediction model and using that model to predict the protein-protein interaction between human and four pathogens. The results show that this graphlet degree vector increases the performance significantly for all pathogens. This suggests that the intraspecies protein-protein interactions should be taken into consideration when developing prediction methods for host-pathogen protein interaction. The results also support the hypothesis that there exists a relationship between a protein's function and the local topology of the PIN.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123522500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Application of Latent Semantic Analysis to Clustering of Cardiovascular Gene Ontology 潜在语义分析在心血管基因本体聚类中的应用

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.71

Charles C. N. Wang, Yu-Liang Lee, P. Sheu, J. Tsai

引用次数: 2

Fine Classification of Human Gut Microbiota by Using Hierarchical Clustering Approach 基于层次聚类方法的人体肠道微生物群精细分类

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.33

Tzu-Fan Chen, Rong-Ming Chen, J. Tsai, Rouh-Mei Hu

{"title":"Fine Classification of Human Gut Microbiota by Using Hierarchical Clustering Approach","authors":"Tzu-Fan Chen, Rong-Ming Chen, J. Tsai, Rouh-Mei Hu","doi":"10.1109/BIBE.2016.33","DOIUrl":"https://doi.org/10.1109/BIBE.2016.33","url":null,"abstract":"Human microbiota account for 1-3 % total human body mass. The gastro-intestinal tract, especially the gut, is rich in different microorganisms, which play important role in our health and diseases. Understanding our gut microbiome may help us to increase the precision of disease prediction and treatment. Traditional culture-based methods are time-consuming, expensive and incomplete. The 16S rRNA metagenomic approach provided a simple and culture-independent way to get more information of gut microbiota. In this study, we analyzed 30 human stool microbiome samples. The hierarchical clustering method was applied to classify the enterotypes. The results showed that: (1) There is a positive correlation between the original NGS data volume, rRNA read number and microbiota diversity. (2) Some bacterial genera presented dominantly in human gut, so that a sufficient sequencing depth is important to identify the minor microbiota component. (3) Bacteroides, Lachnospiracea_incertae_sedis and Ruminococcus2 are the most frequently presented genera. Bacteroides, Prevotella and Alistipes are the most abundant genera. (4) Clustering result showed that there are four main enterotypes: Parabacteroides, Prevotella, Ruminococcus, and Bacterioides. We can still divide Parabacteroides into 3 subclasses according to the composition of bacteria.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125979789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Computational Approach for Blood Flow Analysis in the Densely Coiled Cerebral Aneurysm 密集卷曲脑动脉瘤血流分析的计算方法

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.22

T. Otani, Satoshi Ii, S. Wada, T. Shigematsu, T. Fujinaka, T. Ozaki, M. Hirata

{"title":"A Computational Approach for Blood Flow Analysis in the Densely Coiled Cerebral Aneurysm","authors":"T. Otani, Satoshi Ii, S. Wada, T. Shigematsu, T. Fujinaka, T. Ozaki, M. Hirata","doi":"10.1109/BIBE.2016.22","DOIUrl":"https://doi.org/10.1109/BIBE.2016.22","url":null,"abstract":"Computational fluid dynamics (CFD) study of the blood flow in the coiled cerebral aneurysm is one of powerful tools to explore the treatment mechanism of the endovascular coiling. Although several computational techniques were proposed to represent the realistic coil configuration in the aneurysm for the CFD studies, the CFD methodology for the blood flow analysis in the densely coiled aneurysm is still not fully discussed. The present study develops a CFD approach for the blood flow analysis in the densely coiled cerebral aneurysm without unstructured volume mesh creation. Patient-specific aneurysm geometry with realistic coil configuration was implicitly represented in a Cartesian-grid by using the volume of fraction (VOF) function. A Cartesian-grid CFD simulation was conducted in a finite difference manner with using the VOF function by the method of Weymouth and Yue (J. Compt. Phys., 2011). We conducted that two cases of numerical example of the blood flow analysis in the aneurysm prior to the coiling and after coiling with the packing density of 27%. These examples clearly exhibited that the developed CFD framework successfully resolved the fine flow characteristics around coils in the aneurysm despite the absence of explicit coil surface.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"13 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115826391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Dynamic programming for clinical baseline matching and its application to anti-hepatitis B research 临床基线匹配的动态规划及其在抗乙型肝炎研究中的应用

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.72

Kung-Hao Liang

{"title":"Dynamic programming for clinical baseline matching and its application to anti-hepatitis B research","authors":"Kung-Hao Liang","doi":"10.1109/BIBE.2016.72","DOIUrl":"https://doi.org/10.1109/BIBE.2016.72","url":null,"abstract":"Clinical baseline matching is a critical step in the process of transforming real-world clinical records into novel medical knowledge, more precise diagnosis and efficacious treatments. Conventionally, the baseline matching was performed by heuristic methods or even manually. Here, a baseline-matching algorithm called \"dynamite\" was proposed using the dynamic programming technique. This algorithm minimizes the discrepancy of values of clinical variables or propensity scores between two patient groups in the study, while at the same time includes as many patients as possible so as to maximize statistical power. This algorithm was applied to an anti-hepatitis B research where two classes of approved drugs, peginterferon and nucleos(t)ide reverse transcription inhibitors (NRTI), were compared in terms of their protective effect in patients against hepatocellular carcinoma (HCC). Patients treated by the two classes of medications were retrospectively recruited from clinical records. Initially, age and HBeAg positivity were significantly different between candidate study subjects in the two treatment groups, with 153 and 177 patients respectively. Using the baseline-matching algorithm, the baseline characteristics of the two included patient groups, each comprised 120 patients, were well matched. Longitudinal analysis showed that the peginterferon-treated group achieved better HCC-free survival than the NRTI-treated groups (P = 0.0087293).","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124265174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Chitosan on Motility of Bacteria-Driven Liposomal Microrobots 壳聚糖对细菌驱动脂质体微机器人运动性能的影响

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.20

Van Du Nguyen, Jiwon Han, Shaohui Zheng, Viet Ha Le, Seung Yoon Song, Jong-Oh Park, Sukho Park

{"title":"Effect of Chitosan on Motility of Bacteria-Driven Liposomal Microrobots","authors":"Van Du Nguyen, Jiwon Han, Shaohui Zheng, Viet Ha Le, Seung Yoon Song, Jong-Oh Park, Sukho Park","doi":"10.1109/BIBE.2016.20","DOIUrl":"https://doi.org/10.1109/BIBE.2016.20","url":null,"abstract":"This study proposes a prototype of bacteria-based microrobots using chitosan-coated liposomes attached to a Salmonella enteritidis bacterial strain. The attachment of the liposome and the bacteria is performed by interaction between the positive charge surface of the liposomes and the gram-negative bacteria. The liposomes are fabricated using hydration method to obtain the average diameter of 10 um and they are coated with chitosan. The chitosan coating is shown to have effect on motility of the microrobots. First, the bacteria cannot attach to chitosan-uncoated liposomes, but they can easily adhere to the chitosan-coated liposomes. Second, when the concentration of chitosan increases from 0.1% to 0.5%, average velocity of the microrobots increases from 1.20±0.12 um/s to 3.25±0.35 um/s. However, when chitosan concentration increases to 1% the average velocity of the microrobots slightly decreases from 3.25±0.35 um/s to 3.17±0.33 um/s, respectively. The study suggests that using chitosan coating can be a potential method for further development of therapeutic bacteria-based liposomal microrobots.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125834344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Patient-Specific Blood Flows Simulation on Cerebral Aneurysm Based on Physically Consistency Feedback Control 基于物理一致性反馈控制的脑动脉瘤患者特异性血流模拟

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.32

M. Adib, Satoshi, Yoshiyuki Watanabe, S. Wada

引用次数: 3